Retrieval Augmented Generation (RAG) is a powerful technique to provide real time, domain-specific context to the LLM to improve accuracy of responses. RAG doesn't require the addition of sensitive data to the model, but still requires application developers to address security and privacy of user and company data. In this session, you will learn about security implications of RAG workloads and how to architect your applications to handle user identity and to control data access.

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